Wednesday

In the last 10 years, exoplanet science has evolved from the discovery of exoplanets to the characterisation of their atmospheres. Thanks to Hubble and Spitzer, we now have access to the atmospheric characteristics of about 60 planets. In the next decade, another revolution will occur. Next-generation space telescopes such as JWST and Ariel will come online and obtain high-quality spectra for thousands of exoplanets, constraining atmospheric properties such as chemistry, thermal structure, cloud properties or even dynamics. The influx of data will allow large scale population studies of atmospheres and unravel the main processes driving planetary formation and evolution. This revolution will hopefully enable us to answer some of the most fundamental questions in the field.
In this context, we developed Alfnoor, a code that solves the inverse problem for large exoplanet populations, retrieving atmospheric information from the telescope observations. Alfnoor expands the retrieval capabilities of the retrieval code TauREx3. In recent work, we used Alfnoor, benefiting from the extensive DIRAC computing resources, to simulate the performances of the Ariel Space mission. We demonstrated the ability of the mission to recover trends between atmospheric properties of these worlds and highlighted the limits of the instrument.